Graphical Optimization Method for Symmetrical Bidirectional Corridor Progression

The graphical progression method can obtain grand coordinated schemes with minimal computational complexity. However, there is no standardized solution for this method, and only a few related studies have been found thus far. Therefore, based on the in-depth discussion of the graphical optimization theory mechanism, a process-oriented and high-efficiency graphical method for symmetrical bidirectional corridor progression is proposed in this study. A two-round rotation transformation optimization process of the progression trajectory characteristic lines (PTC lines) is innovatively proposed. By establishing the updated judgment criteria for coordinated mode, the first round of PTC line rotation transformation realizes the optimization of coordinated modes and initial offsets. Giving the conditions for stopping rotation transformation and determining rotation points, rotation directions, and rotation angles, the second round of PTC line rotation transformation achieves the final optimization of the common signal cycle and offsets. The case study shows that the proposed graphical method can obtain the optimal progression effect through regular graphing and solving, although it can also be solved by highly efficient programming.

Modeling and Optimization of a Novel ScAlN-Based MEMS Scanning Mirror with Large Static and Dynamic Two-Axis Tilting Angles

The piezoelectric MEMS (micro-electro-mechanical systems) scanning mirrors are in a great demand for numerous optoelectronic applications. However, the existing actuation strategies are severely limited for poor compatibility with CMOS process, non-linear control, insufficient mirror size and small angular travel. In this paper, a novel, particularly efficient ScAlN-based piezoelectric MEMS mirror with a pupil size of 10 mm is presented. The MEMS mirror consists of a reflection mirror plate, four meandering springs with mechanical rotation transformation, and eight right-angle trapezoidal actuators designed in Union Jack-shaped form. Theoretical modeling, simulations and comparative analysis have been investigated for optimizing two different device designs. For Device A with a 1 mm-length square mirror, the orthogonal and diagonal static tilting angles are ±36.2°@200 VDC and ±36.2°@180 VDC, respectively, and the dynamic tilting angles increases linearly with the driving voltage. Device B with a 10 mm-length square mirror provides the accessible tilting angles of ±36.0°@200 VDC and ±35.9°@180 VDC for horizontal and diagonal actuations, respectively. In the dynamic actuation regime, the orthogonal and diagonal tilting angles at 10 Hz are ±8.1°/Vpp and ±8.9°/Vpp, respectively. This work confirmed that the Union Jack-shaped arrangement of trapezoidal actuators is a promising option for designing powerful optical devices.

Modelling Insight to Ball Eyes for Higher Dimensional Hyperspace Vision

To understand this complicated conceptual idea let me begin first with the definition of VISION and then after DIMENSIONS. The Vision is ability to acquire surrounding with input light, shapes, places, color to brain to create animated CONSCIOUSNESS in the help of Brain call Observable Life, Planet, Universe and Multiverse. Equally Vision also important to grow Brain Intelligence and Control to enhance, develop and shape planet earth and at present observable Universe. Now I would like to define term Dimensions as the ability of Eyes to scan surrounding available Vision with Left, Right, Top, Bottom, Reflection, Rotation, Transformation, Spinning and Diagonal with all possible angles and geometry and provide data to Brain to create high definition Consciousness of environment, planet, universe and multiverse....

Inspection System for Vehicle Headlight Defects Based on Convolutional Neural Network

This paper proposes a method to detect the defects in the region of interest (ROI) based on a convolutional neural network (CNN) after alignment (position and rotation calibration) of a manufacturer’s headlights to determine whether the vehicle headlights are defective. The results were compared with an existing method for distinguishing defects among the previously proposed methods. One hundred original headlight images were acquired for each of the two vehicle types for the purpose of this experiment, and 20,000 high quality images and 20,000 defective images were obtained by applying the position and rotation transformation to the original images. It was found that the method proposed in this paper demonstrated a performance improvement of more than 0.1569 (15.69% on average) as compared to the existing method.

Pruning Multilayered ELM Using Cholesky Factorization and Givens Rotation Transformation

Extreme learning machine is originally proposed for the learning of the single hidden layer feedforward neural network to overcome the challenges faced by the backpropagation (BP) learning algorithm and its variants. Recent studies show that ELM can be extended to the multilayered feedforward neural network in which the hidden node could be a subnetwork of nodes or a combination of other hidden nodes. Although the ELM algorithm with multiple hidden layers shows stronger nonlinear expression ability and stability in both theoretical and experimental results than the ELM algorithm with the single hidden layer, with the deepening of the network structure, the problem of parameter optimization is also highlighted, which usually requires more time for model selection and increases the computational complexity. This paper uses Cholesky factorization strategy and Givens rotation transformation to choose the hidden nodes of MELM and obtains the number of nodes more suitable for the network. First, the initial network has a large number of hidden nodes and then uses the idea of ridge regression to prune the nodes. Finally, a complete neural network can be obtained. Therefore, the ELM algorithm eliminates the need to manually set nodes and achieves complete automation. By using information from the previous generation’s connection weight matrix, it can be evitable to re-calculate the weight matrix in the network simplification process. As in the matrix factorization methods, the Cholesky factorization factor is calculated by Givens rotation transform to achieve the fast decreasing update of the current connection weight matrix, thus ensuring the numerical stability and high efficiency of the pruning process. Empirical studies on several commonly used classification benchmark problems and the real datasets collected from coal industry show that compared with the traditional ELM algorithm, the pruning multilayered ELM algorithm proposed in this paper can find the optimal number of hidden nodes automatically and has better generalization performance.

Effect of passenger uncertainty on the inertial properties of a railway coach

The rotation transformation matrix and translation transformation matrix are derived. They are combined to study the variation of inertial properties of the loaded coach with seating and standing passengers. After that, a CRH2 (China Railway Highspeed) motor coach and Chinese adults in statistical terms are illustrated for precise modelling. It is indicated that CG (Center of Gravity) positions and moments of inertia are all close to linear varying with passenger numbers but at different slopes before and after full-load. It is also found that yaw moment of inertia and pitch moment of inertia are highly correlated. The mass has larger correlation on CG z than CG x and CG y, and larger correlation on roll moment of inertia than yaw and pitch moment of inertia. It may offer some instructions and reference for more realistic simulation of railway vehicle dynamics and measure experiments.

Crack identification in cyclic symmetric structures based on relative indicators of frequency separation

Cyclic symmetric structures are an important class of structures in the fields of civil and mechanical engineering. In order to avoid accidents due to cracks in such structures, an effective method for crack identification is presented in this paper. First, the dynamic model of cyclic symmetric structures with gapless cracks is developed using a structure's sector model and rotation transformation. Then, the effects of cracks on the free vibration characteristics of a cracked cyclic symmetric structure are addressed, with particular interests in the distortion of mode shapes and the shift and split of natural frequencies. On the basis of crack-induced phenomena, an effective method based on relative indicators of frequency separation is developed for quantitative crack identification. Numerical results illustrate that the relative indicators are sensitive to small cracks and insensitive to the predicting model used during analysis. Finally, the method is validated by experiments conducted on an impeller-shaft assembly. The results show the effectiveness of the frequency separation indicators in crack identification in cyclically symmetric structures.